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. 2021 Jan 15:766:145145.
doi: 10.1016/j.gene.2020.145145. Epub 2020 Sep 14.

Serum CCL17 level becomes a predictive marker to distinguish between mild/moderate and severe/critical disease in patients with COVID-19

Masaya Sugiyama  1 , Noriko Kinoshita  2 , Satoshi Ide  2 , Hidetoshi Nomoto  2 , Takato Nakamoto  2 , Sho Saito  2 , Masahiro Ishikane  2 , Satoshi Kutsuna  2 , Kayoko Hayakawa  2 , Masao Hashimoto  3 , Manabu Suzuki  3 , Shinyu Izumi  3 , Masayuki Hojo  3 , Kiyoto Tsuchiya  4 , Hiroyuki Gatanaga  4 , Jin Takasaki  3 , Masahide Usami  5 , Toshikazu Kano  6 , Hidekatsu Yanai  7 , Nao Nishida  8 , Tatsuya Kanto  9 , Haruhito Sugiyama  3 , Norio Ohmagari  10 , Masashi Mizokami  8
Affiliations

Serum CCL17 level becomes a predictive marker to distinguish between mild/moderate and severe/critical disease in patients with COVID-19

Masaya Sugiyama et al. Gene. .

Abstract

COVID-19, a novel coronavirus-related illness, has spread worldwide. Patients with apparently mild/moderate symptoms can suddenly develop severe pneumonia. Therefore, almost all COVID-19 patients require hospitalization, which can reduce limited medical resources in addition to overwhelming medical facilities. To identify predictive markers for the development of severe pneumonia, a comprehensive analysis of serum chemokines and cytokines was conducted using serial serum samples from COVID-19 patients. The expression profiles were analyzed along the time axis. Serum samples of common diseases were enrolled from a BioBank to confirm the usefulness of predictive markers. Five factors, IFN-λ3, IL-6, IP-10, CXCL9, and CCL17, were identified as predicting the onset of severe/critical symptoms. The factors were classified into two categories. Category A included IFN-λ3, IL-6, IP-10, and CXCL9, and their values surged and decreased rapidly before the onset of severe pneumonia. Category B included CCL17, which provided complete separation between the mild/moderate and the severe/critical groups at an early phase of SARS-CoV-2 infection. The five markers provided a high predictive value (area under the receiver operating characteristic curve (AUROC): 0.9-1.0, p < 0.001). Low expression of CCL17 was specifically observed in pre-severe COVID-19 patients compared with other common diseases, and the predictive ability of CCL17 was confirmed in validation samples of COVID-19. The factors identified could be promising prognostic markers to distinguish between mild/moderate and severe/critical patients, enabling triage at an early phase of infection, thus avoiding overwhelming medical facilities.

Keywords: CCL17; COVID-19; CXCL9; IFN-λ3; IL-6; IP-10; Predictive marker.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Dynamics of CCL17, IFN-λ3, IL-6, IP-10, and CXCL9 in COVID-19 patients. Serial serum levels of each factor are shown in 16 mild/moderate and 12 severe/critical patients. Mild/moderate cases are shown by the blue line. Severe cases are shown by the red line. Critical cases are shown by the black line.
Fig. 2
Fig. 2
Receiver operating characteristic (ROC) curves for the highest area under the curve (AUC) values. ROC curves are analyzed to determine the cut-off point for each factor. The arrow shows the cut-off point of each factor. AUC, p value, sensitivity, and specificity are shown. All p values are less than 0.001.
Fig. 3
Fig. 3
Comparison of 5 predictive markers between COVID-19 and common diseases. Five predictive markers for the onset of severe/critical disease are compared among common diseases. The p value was calculated between severe/critical and others, and is ** p < 0.005 and *** p < 0.001. CHC: Chronic hepatitis C, CAP: Child and Adolescent Psychiatry, T2DM: type 2 diabetes mellitus, CRF: chronic renal failure, CHF: chronic heart failure, IP: interstitial pneumonia, RA: rheumatoid arthritis.
Fig. 4
Fig. 4
Validation study and combined analysis of CCL17. A) A total of 58 independent samples were enrolled in the validation study. CCL17 data were collected at an early phase of hospitalization. The cut-off value, 87.5 pg/mL, is used for the validation samples. B) ROC curve analysis using both screening and validation samples. The combined cut-off value is 95.0 pg/mL. C) The combined cut-off value is used for all samples of both screening and validation samples. PPV: positive predictive value, NPV: negative predictive value.
See this image and copyright information in PMC

Comment in

  • Letter from Japan.
    Kan-O K. Kan-O K. Respirology. 2021 Feb;26(2):206-207. doi: 10.1111/resp.13986. Epub 2020 Dec 2. Respirology. 2021. PMID: 33289211 Free PMC article. No abstract available.

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